Deaths from lung cancer are the highest of all cancers in North America and elsewhere and, because of the long incubation time, are likely to remain so for the foreseeable future. Furthermore, although the 5-year survival rate of stage I lung cancer is 60-70%, later stage disease has a very poor prognosis. Accurate detection of asymptomatic early stage lung cancer in individuals at risk is currently unreliable. A better understanding of the basic biochemistry of lung cancers is a prerequisite to mechanism-based reliable early detection of the disease, and to improved approaches to treatment. The very complexity of the transformed cells, and the variable host-tumor interactions, makes the problem refractory to any single approach. A systems biochemistry approach in which lung cancers are studied at the mechanistic level in the laboratory, in mouse models and in human subjects offers the opportunity to address the complexity of cancer development and progression. The use of stable isotope resolved metabolomics provides the necessary direct biochemical information about lung cancer with minimal processing that is not otherwise available. This program will address the problem in a 3-pronged approach, based on the following integrated projects: Project 1: Cellular Systems Biochemistry. Microenvironmental nutrient availability and immune modulation in lung cancer cells. Project 2; Preclinical Systems Biochemistry. Using SIRM in Human NSCLC xenograft mouse to determine biochemical mechanisms of immunomodulator -glucan. Project 3: Translational Systems Biochemistry. Molecular mechanisms of NSCLC and response to -glucan by SIRM. The three projects will use a common mechanistic approach to understanding cancer biochemistry namely stable isotope resolved metabolomics (SIRM) that we have been developing over the last eight years. The analytical requirements will be met in the SIRM Analytical Core, which also supplies the necessary sample handling and bioinformatics support for the three projects. Core A provides overall administrative support.